-------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  /Users/rodoncas/Dropbox/Holocaust_Legacy_Paper/Analysis/Replication_R&P/output.log
  log type:  text
 opened on:  17 Oct 2019, 19:50:02

. 
. 
. 
. ********************************************************************************
. *
. *               PREPARE DATASET FOR ANALYSIS
. *
. ********************************************************************************
. 
. 
. *open distances data
. use "Files/just_AGS_distance_camps.dta", clear

. 
. 
. *We first need to drop a few repeated observations
. sort ags

. quietly by ags:  gen dup = cond(_N==1,0,_n)

. *browse if dup==1
. drop if dup==1
(132 observations deleted)

. drop dup

. 
. 
. *Merge the distances file with additional files
. rename ags ags_num

. gen str ags = string(ags_num,"%08.0f") /*needs to have a leading zero*/

. 
. *Merge it with historical controls
. merge 1:1 ags using "Files/controls_historical_at_modern_spatial_level_withid.dta"

    Result                           # of obs.
    -----------------------------------------
    not matched                             0
    matched                            11,379  (_merge==3)
    -----------------------------------------

. drop _merge

. 
. *merge with election results 
. merge 1:1 ags using "Files/Second_and_First_2013_12.12.2017.dta"
(note: variable ags was str8, now str12 to accommodate using data's values)

    Result                           # of obs.
    -----------------------------------------
    not matched                           262
        from master                       225  (_merge==1)
        from using                         37  (_merge==2)

    matched                            11,154  (_merge==3)
    -----------------------------------------

. 
end of do-file

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. egen p_radical_right_total = rowtotal(SECOND_NPD SECOND_DIERECHTE SECOND_REP SECOND_proDeutschland)

. gen p_radical_right = (p_radical_right_total*100)/Second_total_cast
(226 missing values generated)

. 
end of do-file

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. 
. *encode Land
. encode Land, gen(land_num) 

. 
. *generate log of distance
. gen log_dist = log(distance_nearest_camp)
(37 missing values generated)

. 
. *gen % voting for spd, cdu and other parties
. gen p_cdu = (SECOND_CDU*100)/Second_total_cast
(226 missing values generated)

. gen p_spd = (SECOND_SPD*100)/Second_total_cast
(226 missing values generated)

. gen p_fdp = (SECOND_FDP*100)/Second_total_cast
(226 missing values generated)

. gen p_dielinke = (SECOND_DIELINKE*100)/Second_total_cast
(226 missing values generated)

. gen p_grune = (SECOND_GRÜNE*100)/Second_total_cast
(226 missing values generated)

. 
. drop _merge

. 
. 
. *Include demographic controls data
. merge 1:1  ags using "Files/demographic_controls.dta"
(label _merge already defined)

    Result                           # of obs.
    -----------------------------------------
    not matched                            82
        from master                        37  (_merge==1)
        from using                         45  (_merge==2)

    matched                            11,379  (_merge==3)
    -----------------------------------------

. 
. *log transform population
. destring density, gen(pop_density)
density: all characters numeric; pop_density generated as int
(224 missing values generated)

. gen log_pop_density = log(1 + pop_density)
(224 missing values generated)

. 
. *Include income tax data
. drop _merge

. merge 1:1  ags using "Files/income_tax_2013.dta"
(note: variable Gemeinde was str3, now str14 to accommodate using data's values)
(note: variable ags was str12, now str14 to accommodate using data's values)

    Result                           # of obs.
    -----------------------------------------
    not matched                         8,935
        from master                     3,306  (_merge==1)
        from using                      5,629  (_merge==2)

    matched                             8,155  (_merge==3)
    -----------------------------------------

. 
. *Include unemployment data
. drop _merge

. merge 1:1  ags using "Files/unemployment_2013.dta"
(note: variable Gemeinde_name was str52, now str58 to accommodate using data's values)

    Result                           # of obs.
    -----------------------------------------
    not matched                         3,307
        from master                     3,307  (_merge==1)
        from using                          0  (_merge==2)

    matched                            13,783  (_merge==3)
    -----------------------------------------

. 
. *Transform population, taxes and employment variable
. destring Pop_total, gen(pop_total)
Pop_total: all characters numeric; pop_total generated as long
(5853 missing values generated)

. gen p_unemployment = (Total_unempl*100)/pop_total
(9,059 missing values generated)

. gen log_p_unemployment = log(1+p_unemployment)
(9,059 missing values generated)

. 
. gen p_employed = (Number_people_subject_inc_tax*100) / pop_total
(9,116 missing values generated)

. gen log_p_employed = log(1+p_employed)
(9,116 missing values generated)

. 
. gen log_revenues = log( total_income_and_salary_tax)
(6,032 missing values generated)

. 
. *Generate east and west dummy
. gen east = 0

. replace east = 1 if land_num==11
(1 real change made)

. replace east = 1 if land_num==12
(419 real changes made)

. replace east = 1 if land_num==13
(780 real changes made)

. replace east = 1 if land_num==14
(438 real changes made)

. replace east = 1 if land_num==15
(223 real changes made)

. replace east = 1 if land_num==16
(878 real changes made)

. 
end of do-file

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. drop _merge

. merge 1:1 ags using "Files/Second_and_First_2017_prel.dta", force
(note: variable Land was byte in the using data, but will be str2 now)
(note: variable RB was byte in the using data, but will be str1 now)
(note: variable Kreis was byte in the using data, but will be str2 now)
(note: variable Gemeinde was int in the using data, but will be str14 now)

    Result                           # of obs.
    -----------------------------------------
    not matched                         6,816
        from master                     6,075  (_merge==1)
        from using                        741  (_merge==2)

    matched                            11,015  (_merge==3)
    -----------------------------------------

. 
. *Create outcomes
. *WITH AFD
. egen p_radical_right_total_17 = rowtotal(SECOND_AfD_2017 SECOND_NPD_2017 SECOND_DIERECHTE_2017)

. gen p_radical_right_17 = (p_radical_right_total_17*100)/Second_total_cast_2017
(6,077 missing values generated)

. 
. *WITHOUT AFD
. egen p_radical_right_short_17 = rowtotal(SECOND_NPD_2017 SECOND_DIERECHTE_2017)

. gen p_radical_right_17b = (p_radical_right_short_17*100)/Second_total_cast_2017
(6,077 missing values generated)

. 
. *calculate population density
. destring Area, gen(area_num)
Area: all characters numeric; area_num generated as double
(6594 missing values generated)

. gen pop_density_17 = ( Total_eligible_voters_2017 / area_num)
(6,848 missing values generated)

. gen log_pop_density_17 = log(1 + pop_density_17)
(6,848 missing values generated)

. 
end of do-file

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. 
. *set global controls
. global controls_past ///
>         "c.weighted_pnsda_1930 c.weighted_p_jews_25  c.weighted_p_factory_33  i.east"

. 
. global controls_all ///
>         "c.weighted_pnsda_1930 c.weighted_p_jews_25  c.weighted_p_factory_33  c.perc_male c.perc_cath
> ol c.perc_foreign c.log_pop_density i.east"

.         
. 
end of do-file

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. *Define labels to export
. label variable log_dist "Distance to a concentration camp (log)"

. label variable weighted_pnsda_1930 "\% votes NSDA (1930)"

. label variable weighted_p_jews_25 "\% Jewish population (1925)"

. label variable weighted_p_factory_33 "\% factory workers (1933)"

. label variable perc_male "\% men (2013)"

. label variable perc_cathol "\% Catholics (2013)"

. label variable perc_foreign "\% Foreigners (2013)"

. label variable log_pop_density "(Log) Population density (2013)"

. label variable east "East lander"

. 
end of do-file

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. global controls_all_17 ///
>         "c.weighted_pnsda_1930 c.weighted_p_jews_25  c.weighted_p_factory_33  c.perc_male c.perc_cath
> ol c.perc_foreign c.log_pop_density_17 i.east"

. 
end of do-file

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. eststo clear

. 
end of do-file

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. *with AfD
. eststo: reg p_radical log_dist    $controls_all      i.land_num 
note: 16.land_num omitted because of collinearity

      Source |       SS           df       MS      Number of obs   =     9,248
-------------+----------------------------------   F(19, 9228)     =    444.99
       Model |  30150.4698        19  1586.86683   Prob > F        =    0.0000
    Residual |  32907.7516     9,228  3.56607625   R-squared       =    0.4781
-------------+----------------------------------   Adj R-squared   =    0.4771
       Total |  63058.2214     9,247  6.81931668   Root MSE        =    1.8884

---------------------------------------------------------------------------------------
            p_radical |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
             log_dist |  -.0783777   .0296356    -2.64   0.008    -.1364701   -.0202854
  weighted_pnsda_1930 |  -.0095575   .0036906    -2.59   0.010    -.0167919   -.0023232
   weighted_p_jews_25 |   .0056237   .0434002     0.13   0.897    -.0794502    .0906977
weighted_p_factory_33 |   .0079672   .0026308     3.03   0.002     .0028102    .0131241
            perc_male |   .0664602   .0121512     5.47   0.000     .0426411    .0902792
          perc_cathol |    -.02259   .0010745   -21.02   0.000    -.0246963   -.0204837
         perc_foreign |  -.0470104    .006985    -6.73   0.000    -.0607026   -.0333182
      log_pop_density |   .2738974   .0267815    10.23   0.000     .2213997    .3263951
               1.east |   4.945431   .1201588    41.16   0.000     4.709893    5.180969
                      |
             land_num |
                  03  |  -.1849717   .0927495    -1.99   0.046    -.3667811   -.0031622
                  05  |   .4119178   .1411896     2.92   0.004     .1351551    .6886806
                  06  |   2.274415    .140223    16.22   0.000     1.999547    2.549283
                  07  |   2.000259   .1083046    18.47   0.000     1.787958     2.21256
                  08  |   2.307716   .1173573    19.66   0.000      2.07767    2.537762
                  09  |   1.595702   .1050579    15.19   0.000     1.389765    1.801639
                  10  |   2.818703   .4574027     6.16   0.000     1.922093    3.715313
                  12  |  -.6959401   .1360881    -5.11   0.000    -.9627029   -.4291773
                  14  |   1.082407    .132338     8.18   0.000     .8229954    1.341819
                  15  |  -3.296625   .1625495   -20.28   0.000    -3.615258   -2.977992
                  16  |          0  (omitted)
                      |
                _cons |   1.395405   .7324856     1.91   0.057    -.0404285    2.831239
---------------------------------------------------------------------------------------
(est1 stored)

. eststo: reg p_radical c.log_dist##i.east  $controls_all  , vce(cluster land_num)

Linear regression                               Number of obs     =      9,248
                                                F(10, 11)         =    4102.36
                                                Prob > F          =     0.0000
                                                R-squared         =     0.3875
                                                Root MSE          =     2.0449

                                       (Std. Err. adjusted for 12 clusters in land_num)
---------------------------------------------------------------------------------------
                      |               Robust
            p_radical |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
             log_dist |  -.2058015   .0474099    -4.34   0.001      -.31015    -.101453
               1.east |   .5431407   1.489687     0.36   0.722    -2.735637    3.821919
                      |
      east#c.log_dist |
                   1  |   .3571247   .1446595     2.47   0.031     .0387313     .675518
                      |
  weighted_pnsda_1930 |  -.0279211    .012481    -2.24   0.047    -.0553915   -.0004507
   weighted_p_jews_25 |   .4797514   .2149163     2.23   0.047     .0067238     .952779
weighted_p_factory_33 |   .0439154   .0109245     4.02   0.002     .0198707    .0679602
            perc_male |   .0612916   .0233773     2.62   0.024     .0098386    .1127446
          perc_cathol |  -.0135017   .0051262    -2.63   0.023    -.0247845    -.002219
         perc_foreign |  -.0287635   .0228634    -1.26   0.234    -.0790854    .0215585
      log_pop_density |   .3355681   .0895317     3.75   0.003     .1385101    .5326261
                _cons |   1.479883   1.575096     0.94   0.368     -1.98688    4.946646
---------------------------------------------------------------------------------------
(est2 stored)

. *WITHOUT AfD
. eststo: reg p_radical_right log_dist    $controls_all      i.land_num   /*NOT SIGNIFICANT*/
note: 16.land_num omitted because of collinearity

      Source |       SS           df       MS      Number of obs   =     9,248
-------------+----------------------------------   F(19, 9228)     =    502.47
       Model |  9188.51707        19  483.606162   Prob > F        =    0.0000
    Residual |  8881.47266     9,228  .962448272   R-squared       =    0.5085
-------------+----------------------------------   Adj R-squared   =    0.5075
       Total |  18069.9897     9,247  1.95414618   Root MSE        =    .98104

---------------------------------------------------------------------------------------
      p_radical_right |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
             log_dist |   .0100813    .015396     0.65   0.513    -.0200982    .0402608
  weighted_pnsda_1930 |   .0036837   .0019173     1.92   0.055    -.0000747     .007442
   weighted_p_jews_25 |   .1103261   .0225468     4.89   0.000     .0661294    .1545228
weighted_p_factory_33 |   .0111403   .0013667     8.15   0.000     .0084613    .0138194
            perc_male |   .0445035   .0063127     7.05   0.000     .0321293    .0568777
          perc_cathol |  -.0067371   .0005582   -12.07   0.000    -.0078313   -.0056428
         perc_foreign |  -.0183477   .0036288    -5.06   0.000    -.0254609   -.0112345
      log_pop_density |  -.0732829   .0139133    -5.27   0.000    -.1005559   -.0460098
               1.east |   3.111126   .0624236    49.84   0.000     2.988762     3.23349
                      |
             land_num |
                  03  |   .4240944   .0481842     8.80   0.000     .3296427    .5185461
                  05  |   .8053165   .0733493    10.98   0.000     .6615357    .9490974
                  06  |   .9766726   .0728471    13.41   0.000     .8338761    1.119469
                  07  |   1.116441   .0562653    19.84   0.000     1.006149    1.226734
                  08  |    1.24419   .0609682    20.41   0.000     1.124679    1.363701
                  09  |   1.237572   .0545786    22.68   0.000     1.130586    1.344558
                  10  |   1.733214    .237625     7.29   0.000     1.267416    2.199011
                  12  |  -.0881523   .0706991    -1.25   0.212    -.2267381    .0504335
                  14  |   .6519663   .0687508     9.48   0.000     .5171995    .7867331
                  15  |  -.9222011    .084446   -10.92   0.000    -1.087734   -.7566683
                  16  |          0  (omitted)
                      |
                _cons |  -1.822297   .3805331    -4.79   0.000    -2.568226   -1.076367
---------------------------------------------------------------------------------------
(est3 stored)

. eststo: reg p_radical_right c.log_dist##i.east  $controls_all i.land_num , vce(cluster land_num) /*SI
> GNIFICANT*/
note: 16.land_num omitted because of collinearity

Linear regression                               Number of obs     =      9,248
                                                F(8, 11)          =          .
                                                Prob > F          =          .
                                                R-squared         =     0.5090
                                                Root MSE          =     .98058

                                       (Std. Err. adjusted for 12 clusters in land_num)
---------------------------------------------------------------------------------------
                      |               Robust
      p_radical_right |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
             log_dist |  -.0120693   .0382704    -0.32   0.758     -.096302    .0721634
               1.east |   1.999663   .4435422     4.51   0.001     1.023433    2.975892
                      |
      east#c.log_dist |
                   1  |   .1195864    .050058     2.39   0.036     .0094095    .2297634
                      |
  weighted_pnsda_1930 |   .0034954    .009662     0.36   0.724    -.0177705    .0247613
   weighted_p_jews_25 |   .1130334   .0600964     1.88   0.087    -.0192379    .2453047
weighted_p_factory_33 |   .0114171   .0055516     2.06   0.064     -.000802    .0236362
            perc_male |   .0441075   .0097464     4.53   0.001     .0226558    .0655591
          perc_cathol |  -.0067374    .003258    -2.07   0.063    -.0139082    .0004334
         perc_foreign |  -.0188299   .0103043    -1.83   0.095    -.0415094    .0038497
      log_pop_density |  -.0728245   .0379898    -1.92   0.082    -.1564394    .0107904
                      |
             land_num |
                  03  |   .4184892   .0797008     5.25   0.000      .243069    .5939094
                  05  |   .8009163   .2328264     3.44   0.006     .2884688    1.313364
                  06  |   .9646042   .1812334     5.32   0.000     .5657123    1.363496
                  07  |   1.111031    .255528     4.35   0.001     .5486174    1.673444
                  08  |    1.23285   .2159334     5.71   0.000     .7575839    1.708116
                  09  |   1.228206   .2685421     4.57   0.001     .6371491    1.819264
                  10  |   1.721117   .2839551     6.06   0.000     1.096136    2.346098
                  12  |  -.0865944   .0465515    -1.86   0.090    -.1890536    .0158648
                  14  |    .673476   .0361377    18.64   0.000     .5939376    .7530145
                  15  |  -.9186716   .0476291   -19.29   0.000    -1.023502   -.8138407
                  16  |          0  (omitted)
                      |
                _cons |  -1.597227   .7337212    -2.18   0.052    -3.212136    .0176825
---------------------------------------------------------------------------------------
(est4 stored)

. ****2017
. *with AFD
. eststo: reg p_radical_right_17 log_dist    $controls_all_17      i.land_num, vce(cluster land_num)   
> /*NOT SIGNIFICANT*/
note: 16.land_num omitted because of collinearity

Linear regression                               Number of obs     =      9,117
                                                F(7, 11)          =          .
                                                Prob > F          =          .
                                                R-squared         =     0.7280
                                                Root MSE          =     3.6662

                                       (Std. Err. adjusted for 12 clusters in land_num)
---------------------------------------------------------------------------------------
                      |               Robust
   p_radical_right_17 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
             log_dist |   .0104854    .171818     0.06   0.952    -.3676835    .3886543
  weighted_pnsda_1930 |   .0017866   .0366229     0.05   0.962    -.0788199    .0823932
   weighted_p_jews_25 |  -.5945877   .3776318    -1.57   0.144     -1.42575    .2365742
weighted_p_factory_33 |  -.0011199   .0304709    -0.04   0.971    -.0681858    .0659461
            perc_male |   .2148498   .0345357     6.22   0.000     .1388371    .2908624
          perc_cathol |   -.033204   .0230582    -1.44   0.178    -.0839548    .0175467
         perc_foreign |  -.1263695   .0419476    -3.01   0.012    -.2186954   -.0340435
   log_pop_density_17 |   .3633958   .2319141     1.57   0.145    -.1470436    .8738353
               1.east |   18.15369    .346189    52.44   0.000     17.39174    18.91565
                      |
             land_num |
                  03  |   1.685207   .3333107     5.06   0.000     .9515952    2.418819
                  05  |   2.665279   1.029662     2.59   0.025     .3990074     4.93155
                  06  |   6.691401    .739657     9.05   0.000     5.063427    8.319375
                  07  |   5.218702   1.043112     5.00   0.000     2.922828    7.514576
                  08  |   6.553849   .9675446     6.77   0.000     4.424298      8.6834
                  09  |   7.625768   1.385497     5.50   0.000     4.576308    10.67523
                  10  |   4.135008   1.956312     2.11   0.058    -.1708053    8.440821
                  12  |   -2.84008    .210227   -13.51   0.000    -3.302786   -2.377373
                  14  |   6.072758   .3080737    19.71   0.000     5.394692    6.750824
                  15  |  -4.867615   .1817268   -26.79   0.000    -5.267593   -4.467636
                  16  |          0  (omitted)
                      |
                _cons |  -3.736533   1.503571    -2.49   0.030    -7.045871   -.4271944
---------------------------------------------------------------------------------------
(est5 stored)

. eststo: reg p_radical_right_17 c.log_dist##i.east  $controls_all_17   i.land_num, vce(cluster land_nu
> m) /*SIGNIFICANT*/
note: 16.land_num omitted because of collinearity

Linear regression                               Number of obs     =      9,117
                                                F(8, 11)          =          .
                                                Prob > F          =          .
                                                R-squared         =     0.7292
                                                Root MSE          =     3.6581

                                       (Std. Err. adjusted for 12 clusters in land_num)
---------------------------------------------------------------------------------------
                      |               Robust
   p_radical_right_17 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
             log_dist |  -.1623559   .2105188    -0.77   0.457    -.6257046    .3009927
               1.east |   9.554842   2.718857     3.51   0.005     3.570677    15.53901
                      |
      east#c.log_dist |
                   1  |   .9250144   .2894367     3.20   0.009     .2879684     1.56206
                      |
  weighted_pnsda_1930 |   .0003698   .0367448     0.01   0.992    -.0805048    .0812445
   weighted_p_jews_25 |  -.5735627   .3628261    -1.58   0.142    -1.372138    .2250122
weighted_p_factory_33 |   .0010991   .0300488     0.04   0.971     -.065038    .0672361
            perc_male |   .2117787   .0347125     6.10   0.000     .1353769    .2881805
          perc_cathol |  -.0331818   .0230817    -1.44   0.178    -.0839843    .0176208
         perc_foreign |  -.1302301   .0406502    -3.20   0.008    -.2197005   -.0407597
   log_pop_density_17 |   .3672131   .2292025     1.60   0.137    -.1372583    .8716844
                      |
             land_num |
                  03  |    1.64916   .3293687     5.01   0.000     .9242247    2.374096
                  05  |   2.630025   1.030648     2.55   0.027     .3615846    4.898465
                  06  |   6.596787   .7249328     9.10   0.000     5.001221    8.192354
                  07  |   5.175501   1.048574     4.94   0.000     2.867605    7.483397
                  08  |   6.464841   .9503553     6.80   0.000     4.373123    8.556559
                  09  |   7.551571   1.376394     5.49   0.000     4.522148    10.58099
                  10  |   4.041178   1.920073     2.10   0.059    -.1848746    8.267232
                  12  |  -2.828174   .2070891   -13.66   0.000    -3.283974   -2.372374
                  14  |    6.24723   .2586573    24.15   0.000     5.677929    6.816531
                  15  |  -4.837529   .1795825   -26.94   0.000    -5.232787   -4.442271
                  16  |          0  (omitted)
                      |
                _cons |  -1.985571   1.922518    -1.03   0.324    -6.217005    2.245862
---------------------------------------------------------------------------------------
(est6 stored)

. *WITHOUT AFD    
. eststo: reg p_radical_right_17b log_dist    $controls_all_17      i.land_num  /*NOT SIG*/
note: 16.land_num omitted because of collinearity

      Source |       SS           df       MS      Number of obs   =     9,117
-------------+----------------------------------   F(19, 9097)     =    377.70
       Model |  1209.77871        19  63.6725636   Prob > F        =    0.0000
    Residual |  1533.57731     9,097  .168580556   R-squared       =    0.4410
-------------+----------------------------------   Adj R-squared   =    0.4398
       Total |  2743.35602     9,116  .300938572   Root MSE        =    .41059

---------------------------------------------------------------------------------------
  p_radical_right_17b |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
             log_dist |  -.0106793   .0064943    -1.64   0.100    -.0234096     .002051
  weighted_pnsda_1930 |    .001751   .0008081     2.17   0.030     .0001669    .0033351
   weighted_p_jews_25 |   .0352606   .0094635     3.73   0.000     .0167099    .0538112
weighted_p_factory_33 |   .0020665   .0005766     3.58   0.000     .0009362    .0031968
            perc_male |   .0139644     .00273     5.12   0.000     .0086131    .0193158
          perc_cathol |  -.0021448   .0002351    -9.12   0.000    -.0026057   -.0016839
         perc_foreign |  -.0077616   .0015066    -5.15   0.000    -.0107149   -.0048082
   log_pop_density_17 |  -.0454478   .0058825    -7.73   0.000    -.0569788   -.0339167
               1.east |   1.150561   .0261757    43.96   0.000     1.099251    1.201871
                      |
             land_num |
                  03  |   .0765077   .0207786     3.68   0.000      .035777    .1172383
                  05  |   .1050273   .0308072     3.41   0.001     .0446382    .1654164
                  06  |   .2350288   .0305816     7.69   0.000      .175082    .2949756
                  07  |   .1418301   .0236763     5.99   0.000     .0954192     .188241
                  08  |   .2208446   .0256424     8.61   0.000     .1705797    .2711095
                  09  |     .22777   .0229514     9.92   0.000     .1827801    .2727598
                  10  |   .4335382    .099468     4.36   0.000     .2385587    .6285178
                  12  |  -.3593077   .0296247   -12.13   0.000    -.4173786   -.3012367
                  14  |   .0457358   .0290538     1.57   0.115    -.0112163    .1026878
                  15  |  -.5042677   .0354068   -14.24   0.000     -.573673   -.4348623
                  16  |          0  (omitted)
                      |
                _cons |   -.245584   .1635004    -1.50   0.133    -.5660815    .0749135
---------------------------------------------------------------------------------------
(est7 stored)

. eststo: reg p_radical_right_17b c.log_dist##i.east  $controls_all_17  i.land_num  , vce(cluster land_
> num) /*NOT SIG*/
note: 16.land_num omitted because of collinearity

Linear regression                               Number of obs     =      9,117
                                                F(8, 11)          =          .
                                                Prob > F          =          .
                                                R-squared         =     0.4413
                                                Root MSE          =     .41048

                                       (Std. Err. adjusted for 12 clusters in land_num)
---------------------------------------------------------------------------------------
                      |               Robust
  p_radical_right_17b |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
             log_dist |  -.0178613   .0196099    -0.91   0.382    -.0610224    .0252999
               1.east |   .7932573   .2643099     3.00   0.012     .2115151    1.374999
                      |
      east#c.log_dist |
                   1  |   .0384367   .0288526     1.33   0.210    -.0250675    .1019408
                      |
  weighted_pnsda_1930 |   .0016921   .0019619     0.86   0.407     -.002626    .0060102
   weighted_p_jews_25 |   .0361342    .015877     2.28   0.044     .0011891    .0710793
weighted_p_factory_33 |   .0021587   .0014847     1.45   0.174     -.001109    .0054264
            perc_male |   .0138368    .005284     2.62   0.024     .0022068    .0254668
          perc_cathol |  -.0021439   .0006836    -3.14   0.009    -.0036484   -.0006393
         perc_foreign |   -.007922   .0024642    -3.21   0.008    -.0133457   -.0024983
   log_pop_density_17 |  -.0452892   .0131913    -3.43   0.006     -.074323   -.0162553
                      |
             land_num |
                  03  |   .0750098   .0173394     4.33   0.001     .0368462    .1131735
                  05  |   .1035624   .0473696     2.19   0.051    -.0006973    .2078221
                  06  |   .2310974   .0424744     5.44   0.000     .1376118     .324583
                  07  |    .140035   .0540028     2.59   0.025     .0211757    .2588943
                  08  |   .2171461   .0412331     5.27   0.000     .1263926    .3078995
                  09  |   .2246869   .0488858     4.60   0.001     .1170901    .3322837
                  10  |   .4296394   .0373996    11.49   0.000     .3473234    .5119553
                  12  |   -.358813   .0103753   -34.58   0.000    -.3816488   -.3359771
                  14  |   .0529855   .0088231     6.01   0.000      .033566    .0724051
                  15  |  -.5030175   .0099157   -50.73   0.000    -.5248419   -.4811932
                  16  |          0  (omitted)
                      |
                _cons |  -.1728271   .3338277    -0.52   0.615    -.9075769    .5619227
---------------------------------------------------------------------------------------
(est8 stored)

. 
end of do-file

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. esttab using "models_radicalvoting.tex", title("The effect of distance to a camp on radical right-win
> g voting") ///
> mtitles("M1" "M2" "M3" "M4" "M5") ///
>          nogaps starlevels(+ 0.1 * 0.05 ** 0.01 ) ///
>         b(3) se(3) ar2 replace ///
>          eqlabels(none) nonum  nogaps ///
>         interaction(" * ") compress label 
(output written to models_radicalvoting.tex)

. 
end of do-file

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. reg p_radical c.log_dist##i.east  $controls_all  , vce(cluster land_num)        

Linear regression                               Number of obs     =      9,248
                                                F(10, 11)         =    4102.36
                                                Prob > F          =     0.0000
                                                R-squared         =     0.3875
                                                Root MSE          =     2.0449

                                       (Std. Err. adjusted for 12 clusters in land_num)
---------------------------------------------------------------------------------------
                      |               Robust
            p_radical |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
             log_dist |  -.2058015   .0474099    -4.34   0.001      -.31015    -.101453
               1.east |   .5431407   1.489687     0.36   0.722    -2.735637    3.821919
                      |
      east#c.log_dist |
                   1  |   .3571247   .1446595     2.47   0.031     .0387313     .675518
                      |
  weighted_pnsda_1930 |  -.0279211    .012481    -2.24   0.047    -.0553915   -.0004507
   weighted_p_jews_25 |   .4797514   .2149163     2.23   0.047     .0067238     .952779
weighted_p_factory_33 |   .0439154   .0109245     4.02   0.002     .0198707    .0679602
            perc_male |   .0612916   .0233773     2.62   0.024     .0098386    .1127446
          perc_cathol |  -.0135017   .0051262    -2.63   0.023    -.0247845    -.002219
         perc_foreign |  -.0287635   .0228634    -1.26   0.234    -.0790854    .0215585
      log_pop_density |   .3355681   .0895317     3.75   0.003     .1385101    .5326261
                _cons |   1.479883   1.575096     0.94   0.368     -1.98688    4.946646
---------------------------------------------------------------------------------------

. margins , dydx(east) at(log_dist=(4(1)12))

Average marginal effects                        Number of obs     =      9,248
Model VCE    : Robust

Expression   : Linear prediction, predict()
dy/dx w.r.t. : 1.east

1._at        : log_dist        =           4

2._at        : log_dist        =           5

3._at        : log_dist        =           6

4._at        : log_dist        =           7

5._at        : log_dist        =           8

6._at        : log_dist        =           9

7._at        : log_dist        =          10

8._at        : log_dist        =          11

9._at        : log_dist        =          12

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.east       |  (base outcome)
-------------+----------------------------------------------------------------
1.east       |
         _at |
          1  |   1.971639   .9907136     1.99   0.072    -.2089065    4.152185
          2  |   2.328764    .881324     2.64   0.023      .388983    4.268545
          3  |   2.685889   .7834561     3.43   0.006     .9615136    4.410264
          4  |   3.043013   .7019455     4.34   0.001     1.498042    4.587985
          5  |   3.400138    .643043     5.29   0.000      1.98481    4.815466
          6  |   3.757263   .6132975     6.13   0.000     2.407404    5.107122
          7  |   4.114388   .6169409     6.67   0.000      2.75651    5.472265
          8  |   4.471512   .6534149     6.84   0.000     3.033356    5.909669
          9  |   4.828637   .7177317     6.73   0.000      3.24892    6.408354
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. marginsplot, scheme(s1color) ytitle("% Radical right") title("") ///
>         xtitle("(Log) distance to the nearest concentration camp") ///
>         ytitle("Predicted radical-right support") ///
>         yline(0, lpattern(dash)) name(radical_east, replace)

  Variables that uniquely identify margins: log_dist

. 
end of do-file

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. 
. reg p_radical c.log_dist##i.east  $controls_all  , vce(cluster land_num)        

Linear regression                               Number of obs     =      9,248
                                                F(10, 11)         =    4102.36
                                                Prob > F          =     0.0000
                                                R-squared         =     0.3875
                                                Root MSE          =     2.0449

                                       (Std. Err. adjusted for 12 clusters in land_num)
---------------------------------------------------------------------------------------
                      |               Robust
            p_radical |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
             log_dist |  -.2058015   .0474099    -4.34   0.001      -.31015    -.101453
               1.east |   .5431407   1.489687     0.36   0.722    -2.735637    3.821919
                      |
      east#c.log_dist |
                   1  |   .3571247   .1446595     2.47   0.031     .0387313     .675518
                      |
  weighted_pnsda_1930 |  -.0279211    .012481    -2.24   0.047    -.0553915   -.0004507
   weighted_p_jews_25 |   .4797514   .2149163     2.23   0.047     .0067238     .952779
weighted_p_factory_33 |   .0439154   .0109245     4.02   0.002     .0198707    .0679602
            perc_male |   .0612916   .0233773     2.62   0.024     .0098386    .1127446
          perc_cathol |  -.0135017   .0051262    -2.63   0.023    -.0247845    -.002219
         perc_foreign |  -.0287635   .0228634    -1.26   0.234    -.0790854    .0215585
      log_pop_density |   .3355681   .0895317     3.75   0.003     .1385101    .5326261
                _cons |   1.479883   1.575096     0.94   0.368     -1.98688    4.946646
---------------------------------------------------------------------------------------

. margins east, at(log_dist=(4(1)12))

Predictive margins                              Number of obs     =      9,248
Model VCE    : Robust

Expression   : Linear prediction, predict()

1._at        : log_dist        =           4

2._at        : log_dist        =           5

3._at        : log_dist        =           6

4._at        : log_dist        =           7

5._at        : log_dist        =           8

6._at        : log_dist        =           9

7._at        : log_dist        =          10

8._at        : log_dist        =          11

9._at        : log_dist        =          12

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _at#east |
        1 0  |   7.022407   .2827203    24.84   0.000     6.400144    7.644671
        1 1  |   8.994047   .9723215     9.25   0.000     6.853982    11.13411
        2 0  |   6.816606   .2502119    27.24   0.000     6.265893    7.367319
        2 1  |    9.14537   .8521886    10.73   0.000     7.269716    11.02102
        3 0  |   6.610804   .2231069    29.63   0.000     6.119749    7.101859
        3 1  |   9.296693   .7433713    12.51   0.000     7.660544    10.93284
        4 0  |   6.405003   .2035749    31.46   0.000     5.956938    6.853068
        4 1  |   9.448016   .6515641    14.50   0.000     8.013934     10.8821
        5 0  |   6.199201   .1939181    31.97   0.000     5.772391    6.626012
        5 1  |    9.59934   .5848332    16.41   0.000      8.31213    10.88655
        6 0  |     5.9934   .1956044    30.64   0.000     5.562878    6.423922
        6 1  |   9.750663   .5523435    17.65   0.000     8.534963    10.96636
        7 0  |   5.787598   .2083587    27.78   0.000     5.329004    6.246193
        7 1  |   9.901986   .5600858    17.68   0.000     8.669245    11.13473
        8 0  |   5.581797   .2303497    24.23   0.000       5.0748    6.088793
        8 1  |   10.05331   .6065214    16.58   0.000     8.718364    11.38825
        9 0  |   5.375995   .2592375    20.74   0.000     4.805418    5.946573
        9 1  |   10.20463   .6838126    14.92   0.000     8.699571    11.70969
------------------------------------------------------------------------------

. marginsplot, scheme(s1color) ytitle("% Radical right") title("") ///
>         xtitle("(Log) distance to the nearest concentration camp") ///
>         ytitle("Predicted radical-right support") ///
>         yline(0, lpattern(dash)) name(radical_east, replace)

  Variables that uniquely identify margins: log_dist east

. 
end of do-file

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. reg p_radical c.log_dist##i.east  $controls_all  , robust

Linear regression                               Number of obs     =      9,248
                                                F(10, 9237)       =     427.99
                                                Prob > F          =     0.0000
                                                R-squared         =     0.3875
                                                Root MSE          =     2.0449

---------------------------------------------------------------------------------------
                      |               Robust
            p_radical |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
             log_dist |  -.2058015   .0312577    -6.58   0.000    -.2670736   -.1445294
               1.east |   .5431407   .9211678     0.59   0.555    -1.262552    2.348833
                      |
      east#c.log_dist |
                   1  |   .3571247   .1009417     3.54   0.000     .1592566    .5549927
                      |
  weighted_pnsda_1930 |  -.0279211   .0035812    -7.80   0.000     -.034941   -.0209012
   weighted_p_jews_25 |   .4797514   .0352278    13.62   0.000     .4106971    .5488057
weighted_p_factory_33 |   .0439154   .0023024    19.07   0.000     .0394022    .0484287
            perc_male |   .0612916   .0168981     3.63   0.000     .0281676    .0944155
          perc_cathol |  -.0135017   .0009206   -14.67   0.000    -.0153063   -.0116971
         perc_foreign |  -.0287635   .0087816    -3.28   0.001    -.0459773   -.0115496
      log_pop_density |   .3355681   .0325522    10.31   0.000     .2717587    .3993776
                _cons |   1.479883   .9456924     1.56   0.118     -.373883    3.333649
---------------------------------------------------------------------------------------

. margins east, at(log_dist=(4(1)12))

Predictive margins                              Number of obs     =      9,248
Model VCE    : Robust

Expression   : Linear prediction, predict()

1._at        : log_dist        =           4

2._at        : log_dist        =           5

3._at        : log_dist        =           6

4._at        : log_dist        =           7

5._at        : log_dist        =           8

6._at        : log_dist        =           9

7._at        : log_dist        =          10

8._at        : log_dist        =          11

9._at        : log_dist        =          12

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _at#east |
        1 0  |   7.022407   .1770094    39.67   0.000      6.67543    7.369385
        1 1  |   8.994047   .4916137    18.29   0.000     8.030375    9.957718
        2 0  |   6.816606   .1460635    46.67   0.000     6.530289    7.102923
        2 1  |    9.14537   .3966647    23.06   0.000      8.36782     9.92292
        3 0  |   6.610804    .115286    57.34   0.000     6.384818     6.83679
        3 1  |   9.296693   .3027273    30.71   0.000     8.703281    9.890106
        4 0  |   6.405003   .0848603    75.48   0.000     6.238658    6.571348
        4 1  |   9.448016   .2111561    44.74   0.000     9.034104    9.861929
        5 0  |   6.199201   .0553693   111.96   0.000     6.090665    6.307738
        5 1  |    9.59934   .1271697    75.48   0.000     9.350059     9.84862
        6 0  |     5.9934   .0297381   201.54   0.000     5.935107    6.051693
        6 1  |   9.750663   .0799968   121.89   0.000     9.593851    9.907474
        7 0  |   5.787598   .0256327   225.79   0.000     5.737353    5.837844
        7 1  |   9.901986   .1235677    80.13   0.000     9.659766    10.14421
        8 0  |   5.581797   .0488242   114.32   0.000     5.486091    5.677503
        8 1  |   10.05331   .2068347    48.61   0.000     9.647867    10.45875
        9 0  |   5.375995    .077876    69.03   0.000     5.223341     5.52865
        9 1  |   10.20463   .2982186    34.22   0.000     9.620058    10.78921
------------------------------------------------------------------------------

. marginsplot, scheme(s1color) ytitle("% Radical right") title("") ///
>         xtitle("(Log) distance to the nearest concentration camp") ///
>         ytitle("Predicted radical-right support") ///
>         yline(0, lpattern(dash)) name(radical_east, replace)

  Variables that uniquely identify margins: log_dist east

. 
end of do-file

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. reg p_radical_right_17 c.log_dist##i.east    $controls_all_17   , robust

Linear regression                               Number of obs     =      9,117
                                                F(10, 9106)       =     822.70
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6274
                                                Root MSE          =     4.2885

---------------------------------------------------------------------------------------
                      |               Robust
   p_radical_right_17 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
             log_dist |  -.5184882   .0658863    -7.87   0.000    -.6476401   -.3893362
               1.east |   7.671459   2.214003     3.46   0.001     3.331516     12.0114
                      |
      east#c.log_dist |
                   1  |    .828591   .2415722     3.43   0.001     .3550551    1.302127
                      |
  weighted_pnsda_1930 |  -.0230938   .0073174    -3.16   0.002    -.0374374   -.0087501
   weighted_p_jews_25 |   .3336737   .0724914     4.60   0.000     .1915743    .4757731
weighted_p_factory_33 |   .0835817   .0046851    17.84   0.000     .0743979    .0927654
            perc_male |   .1863658   .0312304     5.97   0.000     .1251472    .2475844
          perc_cathol |   .0082309   .0020615     3.99   0.000     .0041899    .0122719
         perc_foreign |  -.1244345   .0148504    -8.38   0.000    -.1535446   -.0953243
   log_pop_density_17 |   .6753373   .0616805    10.95   0.000     .5544297     .796245
                _cons |  -.3760229   1.809599    -0.21   0.835    -3.923243    3.171197
---------------------------------------------------------------------------------------

. margins east, at(log_dist=(4(1)12))

Predictive margins                              Number of obs     =      9,117
Model VCE    : Robust

Expression   : Linear prediction, predict()

1._at        : log_dist        =           4

2._at        : log_dist        =           5

3._at        : log_dist        =           6

4._at        : log_dist        =           7

5._at        : log_dist        =           8

6._at        : log_dist        =           9

7._at        : log_dist        =          10

8._at        : log_dist        =          11

9._at        : log_dist        =          12

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _at#east |
        1 0  |   14.30285   .3707379    38.58   0.000     13.57612    15.02958
        1 1  |   25.28867   1.201846    21.04   0.000     22.93279    27.64456
        2 0  |   13.78436   .3053923    45.14   0.000     13.18573      14.383
        2 1  |   25.59878   .9718506    26.34   0.000     23.69373    27.50382
        3 0  |   13.26588    .240342    55.20   0.000     12.79475      13.737
        3 1  |   25.90888   .7439926    34.82   0.000     24.45049    27.36727
        4 0  |   12.74739   .1759152    72.46   0.000     12.40255    13.09222
        4 1  |   26.21898   .5210829    50.32   0.000     25.19754    27.24042
        5 0  |    12.2289   .1131815   108.05   0.000     12.00704    12.45076
        5 1  |   26.52909   .3138487    84.53   0.000     25.91387     27.1443
        6 0  |   11.71041   .0579307   202.15   0.000     11.59685    11.82397
        6 1  |   26.83919   .1855954   144.61   0.000     26.47538      27.203
        7 0  |   11.19192   .0508319   220.18   0.000     11.09228    11.29156
        7 1  |   27.14929   .2817116    96.37   0.000     26.59707    27.70151
        8 0  |   10.67343   .1024393   104.19   0.000     10.47263    10.87424
        8 1  |   27.45939   .4829579    56.86   0.000     26.51269     28.4061
        9 0  |   10.15495   .1645775    61.70   0.000     9.832337    10.47756
        9 1  |    27.7695   .7043481    39.43   0.000     26.38882    29.15018
------------------------------------------------------------------------------

. marginsplot, scheme(s1color) ytitle("% Radical right") title("") ///
>         xtitle("(Log) distance nearest concentration camp") ///
>         ytitle("Predicted radical-right support") ///
>                 title("2017") ///
>          name(afd_2017, replace)        ///
>         plot( , label("West" "East"))

  Variables that uniquely identify margins: log_dist east

. 
end of do-file

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. graph combine afd_2013 afd_2017, scheme(s1color)
afd_2013 is not a memory graph
r(198);

end of do-file

r(198);

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. 
. reg p_radical c.log_dist##i.east  $controls_all  , robust

Linear regression                               Number of obs     =      9,248
                                                F(10, 9237)       =     427.99
                                                Prob > F          =     0.0000
                                                R-squared         =     0.3875
                                                Root MSE          =     2.0449

---------------------------------------------------------------------------------------
                      |               Robust
            p_radical |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
             log_dist |  -.2058015   .0312577    -6.58   0.000    -.2670736   -.1445294
               1.east |   .5431407   .9211678     0.59   0.555    -1.262552    2.348833
                      |
      east#c.log_dist |
                   1  |   .3571247   .1009417     3.54   0.000     .1592566    .5549927
                      |
  weighted_pnsda_1930 |  -.0279211   .0035812    -7.80   0.000     -.034941   -.0209012
   weighted_p_jews_25 |   .4797514   .0352278    13.62   0.000     .4106971    .5488057
weighted_p_factory_33 |   .0439154   .0023024    19.07   0.000     .0394022    .0484287
            perc_male |   .0612916   .0168981     3.63   0.000     .0281676    .0944155
          perc_cathol |  -.0135017   .0009206   -14.67   0.000    -.0153063   -.0116971
         perc_foreign |  -.0287635   .0087816    -3.28   0.001    -.0459773   -.0115496
      log_pop_density |   .3355681   .0325522    10.31   0.000     .2717587    .3993776
                _cons |   1.479883   .9456924     1.56   0.118     -.373883    3.333649
---------------------------------------------------------------------------------------

. margins east, at(log_dist=(4(1)12))

Predictive margins                              Number of obs     =      9,248
Model VCE    : Robust

Expression   : Linear prediction, predict()

1._at        : log_dist        =           4

2._at        : log_dist        =           5

3._at        : log_dist        =           6

4._at        : log_dist        =           7

5._at        : log_dist        =           8

6._at        : log_dist        =           9

7._at        : log_dist        =          10

8._at        : log_dist        =          11

9._at        : log_dist        =          12

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _at#east |
        1 0  |   7.022407   .1770094    39.67   0.000      6.67543    7.369385
        1 1  |   8.994047   .4916137    18.29   0.000     8.030375    9.957718
        2 0  |   6.816606   .1460635    46.67   0.000     6.530289    7.102923
        2 1  |    9.14537   .3966647    23.06   0.000      8.36782     9.92292
        3 0  |   6.610804    .115286    57.34   0.000     6.384818     6.83679
        3 1  |   9.296693   .3027273    30.71   0.000     8.703281    9.890106
        4 0  |   6.405003   .0848603    75.48   0.000     6.238658    6.571348
        4 1  |   9.448016   .2111561    44.74   0.000     9.034104    9.861929
        5 0  |   6.199201   .0553693   111.96   0.000     6.090665    6.307738
        5 1  |    9.59934   .1271697    75.48   0.000     9.350059     9.84862
        6 0  |     5.9934   .0297381   201.54   0.000     5.935107    6.051693
        6 1  |   9.750663   .0799968   121.89   0.000     9.593851    9.907474
        7 0  |   5.787598   .0256327   225.79   0.000     5.737353    5.837844
        7 1  |   9.901986   .1235677    80.13   0.000     9.659766    10.14421
        8 0  |   5.581797   .0488242   114.32   0.000     5.486091    5.677503
        8 1  |   10.05331   .2068347    48.61   0.000     9.647867    10.45875
        9 0  |   5.375995    .077876    69.03   0.000     5.223341     5.52865
        9 1  |   10.20463   .2982186    34.22   0.000     9.620058    10.78921
------------------------------------------------------------------------------

. marginsplot, scheme(s1color) ytitle("% Radical right") title("") ///
>         xtitle("(Log) distance to the nearest concentration camp") ///
>         ytitle("Predicted radical-right support") ///
>         yline(0, lpattern(dash)) name(afd_2013, replace)

  Variables that uniquely identify margins: log_dist east

. 
. reg p_radical_right_17 c.log_dist##i.east    $controls_all_17   , robust

Linear regression                               Number of obs     =      9,117
                                                F(10, 9106)       =     822.70
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6274
                                                Root MSE          =     4.2885

---------------------------------------------------------------------------------------
                      |               Robust
   p_radical_right_17 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
             log_dist |  -.5184882   .0658863    -7.87   0.000    -.6476401   -.3893362
               1.east |   7.671459   2.214003     3.46   0.001     3.331516     12.0114
                      |
      east#c.log_dist |
                   1  |    .828591   .2415722     3.43   0.001     .3550551    1.302127
                      |
  weighted_pnsda_1930 |  -.0230938   .0073174    -3.16   0.002    -.0374374   -.0087501
   weighted_p_jews_25 |   .3336737   .0724914     4.60   0.000     .1915743    .4757731
weighted_p_factory_33 |   .0835817   .0046851    17.84   0.000     .0743979    .0927654
            perc_male |   .1863658   .0312304     5.97   0.000     .1251472    .2475844
          perc_cathol |   .0082309   .0020615     3.99   0.000     .0041899    .0122719
         perc_foreign |  -.1244345   .0148504    -8.38   0.000    -.1535446   -.0953243
   log_pop_density_17 |   .6753373   .0616805    10.95   0.000     .5544297     .796245
                _cons |  -.3760229   1.809599    -0.21   0.835    -3.923243    3.171197
---------------------------------------------------------------------------------------

. margins east, at(log_dist=(4(1)12))

Predictive margins                              Number of obs     =      9,117
Model VCE    : Robust

Expression   : Linear prediction, predict()

1._at        : log_dist        =           4

2._at        : log_dist        =           5

3._at        : log_dist        =           6

4._at        : log_dist        =           7

5._at        : log_dist        =           8

6._at        : log_dist        =           9

7._at        : log_dist        =          10

8._at        : log_dist        =          11

9._at        : log_dist        =          12

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _at#east |
        1 0  |   14.30285   .3707379    38.58   0.000     13.57612    15.02958
        1 1  |   25.28867   1.201846    21.04   0.000     22.93279    27.64456
        2 0  |   13.78436   .3053923    45.14   0.000     13.18573      14.383
        2 1  |   25.59878   .9718506    26.34   0.000     23.69373    27.50382
        3 0  |   13.26588    .240342    55.20   0.000     12.79475      13.737
        3 1  |   25.90888   .7439926    34.82   0.000     24.45049    27.36727
        4 0  |   12.74739   .1759152    72.46   0.000     12.40255    13.09222
        4 1  |   26.21898   .5210829    50.32   0.000     25.19754    27.24042
        5 0  |    12.2289   .1131815   108.05   0.000     12.00704    12.45076
        5 1  |   26.52909   .3138487    84.53   0.000     25.91387     27.1443
        6 0  |   11.71041   .0579307   202.15   0.000     11.59685    11.82397
        6 1  |   26.83919   .1855954   144.61   0.000     26.47538      27.203
        7 0  |   11.19192   .0508319   220.18   0.000     11.09228    11.29156
        7 1  |   27.14929   .2817116    96.37   0.000     26.59707    27.70151
        8 0  |   10.67343   .1024393   104.19   0.000     10.47263    10.87424
        8 1  |   27.45939   .4829579    56.86   0.000     26.51269     28.4061
        9 0  |   10.15495   .1645775    61.70   0.000     9.832337    10.47756
        9 1  |    27.7695   .7043481    39.43   0.000     26.38882    29.15018
------------------------------------------------------------------------------

. marginsplot, scheme(s1color) ytitle("% Radical right") title("") ///
>         xtitle("(Log) distance nearest concentration camp") ///
>         ytitle("Predicted radical-right support") ///
>                 title("2017") ///
>          name(afd_2017, replace)        ///
>         plot( , label("West" "East"))

  Variables that uniquely identify margins: log_dist east

. 
. 
. graph combine afd_2013 afd_2017, scheme(s1color)

. 
end of do-file

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. 
. reg p_radical c.log_dist##i.east  $controls_all  , robust

Linear regression                               Number of obs     =      9,248
                                                F(10, 9237)       =     427.99
                                                Prob > F          =     0.0000
                                                R-squared         =     0.3875
                                                Root MSE          =     2.0449

---------------------------------------------------------------------------------------
                      |               Robust
            p_radical |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
             log_dist |  -.2058015   .0312577    -6.58   0.000    -.2670736   -.1445294
               1.east |   .5431407   .9211678     0.59   0.555    -1.262552    2.348833
                      |
      east#c.log_dist |
                   1  |   .3571247   .1009417     3.54   0.000     .1592566    .5549927
                      |
  weighted_pnsda_1930 |  -.0279211   .0035812    -7.80   0.000     -.034941   -.0209012
   weighted_p_jews_25 |   .4797514   .0352278    13.62   0.000     .4106971    .5488057
weighted_p_factory_33 |   .0439154   .0023024    19.07   0.000     .0394022    .0484287
            perc_male |   .0612916   .0168981     3.63   0.000     .0281676    .0944155
          perc_cathol |  -.0135017   .0009206   -14.67   0.000    -.0153063   -.0116971
         perc_foreign |  -.0287635   .0087816    -3.28   0.001    -.0459773   -.0115496
      log_pop_density |   .3355681   .0325522    10.31   0.000     .2717587    .3993776
                _cons |   1.479883   .9456924     1.56   0.118     -.373883    3.333649
---------------------------------------------------------------------------------------

. margins east, at(log_dist=(4(1)12))

Predictive margins                              Number of obs     =      9,248
Model VCE    : Robust

Expression   : Linear prediction, predict()

1._at        : log_dist        =           4

2._at        : log_dist        =           5

3._at        : log_dist        =           6

4._at        : log_dist        =           7

5._at        : log_dist        =           8

6._at        : log_dist        =           9

7._at        : log_dist        =          10

8._at        : log_dist        =          11

9._at        : log_dist        =          12

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _at#east |
        1 0  |   7.022407   .1770094    39.67   0.000      6.67543    7.369385
        1 1  |   8.994047   .4916137    18.29   0.000     8.030375    9.957718
        2 0  |   6.816606   .1460635    46.67   0.000     6.530289    7.102923
        2 1  |    9.14537   .3966647    23.06   0.000      8.36782     9.92292
        3 0  |   6.610804    .115286    57.34   0.000     6.384818     6.83679
        3 1  |   9.296693   .3027273    30.71   0.000     8.703281    9.890106
        4 0  |   6.405003   .0848603    75.48   0.000     6.238658    6.571348
        4 1  |   9.448016   .2111561    44.74   0.000     9.034104    9.861929
        5 0  |   6.199201   .0553693   111.96   0.000     6.090665    6.307738
        5 1  |    9.59934   .1271697    75.48   0.000     9.350059     9.84862
        6 0  |     5.9934   .0297381   201.54   0.000     5.935107    6.051693
        6 1  |   9.750663   .0799968   121.89   0.000     9.593851    9.907474
        7 0  |   5.787598   .0256327   225.79   0.000     5.737353    5.837844
        7 1  |   9.901986   .1235677    80.13   0.000     9.659766    10.14421
        8 0  |   5.581797   .0488242   114.32   0.000     5.486091    5.677503
        8 1  |   10.05331   .2068347    48.61   0.000     9.647867    10.45875
        9 0  |   5.375995    .077876    69.03   0.000     5.223341     5.52865
        9 1  |   10.20463   .2982186    34.22   0.000     9.620058    10.78921
------------------------------------------------------------------------------

. marginsplot, scheme(s1color) ytitle("% Radical right") title("") ///
>         xtitle("(Log) distance to the nearest concentration camp") ///
>         ytitle("Predicted radical-right support") ///
>                         title("2017") ///
>         yline(0, lpattern(dash)) name(afd_2013, replace) ///
>         plot( , label("West" "East"))

  Variables that uniquely identify margins: log_dist east

. 
. reg p_radical_right_17 c.log_dist##i.east    $controls_all_17   , robust

Linear regression                               Number of obs     =      9,117
                                                F(10, 9106)       =     822.70
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6274
                                                Root MSE          =     4.2885

---------------------------------------------------------------------------------------
                      |               Robust
   p_radical_right_17 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
             log_dist |  -.5184882   .0658863    -7.87   0.000    -.6476401   -.3893362
               1.east |   7.671459   2.214003     3.46   0.001     3.331516     12.0114
                      |
      east#c.log_dist |
                   1  |    .828591   .2415722     3.43   0.001     .3550551    1.302127
                      |
  weighted_pnsda_1930 |  -.0230938   .0073174    -3.16   0.002    -.0374374   -.0087501
   weighted_p_jews_25 |   .3336737   .0724914     4.60   0.000     .1915743    .4757731
weighted_p_factory_33 |   .0835817   .0046851    17.84   0.000     .0743979    .0927654
            perc_male |   .1863658   .0312304     5.97   0.000     .1251472    .2475844
          perc_cathol |   .0082309   .0020615     3.99   0.000     .0041899    .0122719
         perc_foreign |  -.1244345   .0148504    -8.38   0.000    -.1535446   -.0953243
   log_pop_density_17 |   .6753373   .0616805    10.95   0.000     .5544297     .796245
                _cons |  -.3760229   1.809599    -0.21   0.835    -3.923243    3.171197
---------------------------------------------------------------------------------------

. margins east, at(log_dist=(4(1)12))

Predictive margins                              Number of obs     =      9,117
Model VCE    : Robust

Expression   : Linear prediction, predict()

1._at        : log_dist        =           4

2._at        : log_dist        =           5

3._at        : log_dist        =           6

4._at        : log_dist        =           7

5._at        : log_dist        =           8

6._at        : log_dist        =           9

7._at        : log_dist        =          10

8._at        : log_dist        =          11

9._at        : log_dist        =          12

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _at#east |
        1 0  |   14.30285   .3707379    38.58   0.000     13.57612    15.02958
        1 1  |   25.28867   1.201846    21.04   0.000     22.93279    27.64456
        2 0  |   13.78436   .3053923    45.14   0.000     13.18573      14.383
        2 1  |   25.59878   .9718506    26.34   0.000     23.69373    27.50382
        3 0  |   13.26588    .240342    55.20   0.000     12.79475      13.737
        3 1  |   25.90888   .7439926    34.82   0.000     24.45049    27.36727
        4 0  |   12.74739   .1759152    72.46   0.000     12.40255    13.09222
        4 1  |   26.21898   .5210829    50.32   0.000     25.19754    27.24042
        5 0  |    12.2289   .1131815   108.05   0.000     12.00704    12.45076
        5 1  |   26.52909   .3138487    84.53   0.000     25.91387     27.1443
        6 0  |   11.71041   .0579307   202.15   0.000     11.59685    11.82397
        6 1  |   26.83919   .1855954   144.61   0.000     26.47538      27.203
        7 0  |   11.19192   .0508319   220.18   0.000     11.09228    11.29156
        7 1  |   27.14929   .2817116    96.37   0.000     26.59707    27.70151
        8 0  |   10.67343   .1024393   104.19   0.000     10.47263    10.87424
        8 1  |   27.45939   .4829579    56.86   0.000     26.51269     28.4061
        9 0  |   10.15495   .1645775    61.70   0.000     9.832337    10.47756
        9 1  |    27.7695   .7043481    39.43   0.000     26.38882    29.15018
------------------------------------------------------------------------------

. marginsplot, scheme(s1color) ytitle("% Radical right") title("") ///
>         xtitle("(Log) distance nearest concentration camp") ///
>         ytitle("Predicted radical-right support") ///
>                 title("2017") ///
>          name(afd_2017, replace)        ///
>         plot( , label("West" "East"))

  Variables that uniquely identify margins: log_dist east

. 
. 
. graph combine afd_2013 afd_2017, scheme(s1color)

. 
end of do-file

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. reg p_radical c.log_dist##i.east  $controls_all  , robust

Linear regression                               Number of obs     =      9,248
                                                F(10, 9237)       =     427.99
                                                Prob > F          =     0.0000
                                                R-squared         =     0.3875
                                                Root MSE          =     2.0449

---------------------------------------------------------------------------------------
                      |               Robust
            p_radical |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
             log_dist |  -.2058015   .0312577    -6.58   0.000    -.2670736   -.1445294
               1.east |   .5431407   .9211678     0.59   0.555    -1.262552    2.348833
                      |
      east#c.log_dist |
                   1  |   .3571247   .1009417     3.54   0.000     .1592566    .5549927
                      |
  weighted_pnsda_1930 |  -.0279211   .0035812    -7.80   0.000     -.034941   -.0209012
   weighted_p_jews_25 |   .4797514   .0352278    13.62   0.000     .4106971    .5488057
weighted_p_factory_33 |   .0439154   .0023024    19.07   0.000     .0394022    .0484287
            perc_male |   .0612916   .0168981     3.63   0.000     .0281676    .0944155
          perc_cathol |  -.0135017   .0009206   -14.67   0.000    -.0153063   -.0116971
         perc_foreign |  -.0287635   .0087816    -3.28   0.001    -.0459773   -.0115496
      log_pop_density |   .3355681   .0325522    10.31   0.000     .2717587    .3993776
                _cons |   1.479883   .9456924     1.56   0.118     -.373883    3.333649
---------------------------------------------------------------------------------------

. margins east, at(log_dist=(4(1)12))

Predictive margins                              Number of obs     =      9,248
Model VCE    : Robust

Expression   : Linear prediction, predict()

1._at        : log_dist        =           4

2._at        : log_dist        =           5

3._at        : log_dist        =           6

4._at        : log_dist        =           7

5._at        : log_dist        =           8

6._at        : log_dist        =           9

7._at        : log_dist        =          10

8._at        : log_dist        =          11

9._at        : log_dist        =          12

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _at#east |
        1 0  |   7.022407   .1770094    39.67   0.000      6.67543    7.369385
        1 1  |   8.994047   .4916137    18.29   0.000     8.030375    9.957718
        2 0  |   6.816606   .1460635    46.67   0.000     6.530289    7.102923
        2 1  |    9.14537   .3966647    23.06   0.000      8.36782     9.92292
        3 0  |   6.610804    .115286    57.34   0.000     6.384818     6.83679
        3 1  |   9.296693   .3027273    30.71   0.000     8.703281    9.890106
        4 0  |   6.405003   .0848603    75.48   0.000     6.238658    6.571348
        4 1  |   9.448016   .2111561    44.74   0.000     9.034104    9.861929
        5 0  |   6.199201   .0553693   111.96   0.000     6.090665    6.307738
        5 1  |    9.59934   .1271697    75.48   0.000     9.350059     9.84862
        6 0  |     5.9934   .0297381   201.54   0.000     5.935107    6.051693
        6 1  |   9.750663   .0799968   121.89   0.000     9.593851    9.907474
        7 0  |   5.787598   .0256327   225.79   0.000     5.737353    5.837844
        7 1  |   9.901986   .1235677    80.13   0.000     9.659766    10.14421
        8 0  |   5.581797   .0488242   114.32   0.000     5.486091    5.677503
        8 1  |   10.05331   .2068347    48.61   0.000     9.647867    10.45875
        9 0  |   5.375995    .077876    69.03   0.000     5.223341     5.52865
        9 1  |   10.20463   .2982186    34.22   0.000     9.620058    10.78921
------------------------------------------------------------------------------

. marginsplot, scheme(s1color) ytitle("% Radical right") title("") ///
>         xtitle("(Log) distance to the nearest concentration camp") ///
>         ytitle("Predicted radical-right support") ///
>                         title("2013") ///
>         yline(0, lpattern(dash)) name(afd_2013, replace) ///
>         plot( , label("West" "East"))

  Variables that uniquely identify margins: log_dist east

. 
. reg p_radical_right_17 c.log_dist##i.east    $controls_all_17   , robust

Linear regression                               Number of obs     =      9,117
                                                F(10, 9106)       =     822.70
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6274
                                                Root MSE          =     4.2885

---------------------------------------------------------------------------------------
                      |               Robust
   p_radical_right_17 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
             log_dist |  -.5184882   .0658863    -7.87   0.000    -.6476401   -.3893362
               1.east |   7.671459   2.214003     3.46   0.001     3.331516     12.0114
                      |
      east#c.log_dist |
                   1  |    .828591   .2415722     3.43   0.001     .3550551    1.302127
                      |
  weighted_pnsda_1930 |  -.0230938   .0073174    -3.16   0.002    -.0374374   -.0087501
   weighted_p_jews_25 |   .3336737   .0724914     4.60   0.000     .1915743    .4757731
weighted_p_factory_33 |   .0835817   .0046851    17.84   0.000     .0743979    .0927654
            perc_male |   .1863658   .0312304     5.97   0.000     .1251472    .2475844
          perc_cathol |   .0082309   .0020615     3.99   0.000     .0041899    .0122719
         perc_foreign |  -.1244345   .0148504    -8.38   0.000    -.1535446   -.0953243
   log_pop_density_17 |   .6753373   .0616805    10.95   0.000     .5544297     .796245
                _cons |  -.3760229   1.809599    -0.21   0.835    -3.923243    3.171197
---------------------------------------------------------------------------------------

. margins east, at(log_dist=(4(1)12))

Predictive margins                              Number of obs     =      9,117
Model VCE    : Robust

Expression   : Linear prediction, predict()

1._at        : log_dist        =           4

2._at        : log_dist        =           5

3._at        : log_dist        =           6

4._at        : log_dist        =           7

5._at        : log_dist        =           8

6._at        : log_dist        =           9

7._at        : log_dist        =          10

8._at        : log_dist        =          11

9._at        : log_dist        =          12

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _at#east |
        1 0  |   14.30285   .3707379    38.58   0.000     13.57612    15.02958
        1 1  |   25.28867   1.201846    21.04   0.000     22.93279    27.64456
        2 0  |   13.78436   .3053923    45.14   0.000     13.18573      14.383
        2 1  |   25.59878   .9718506    26.34   0.000     23.69373    27.50382
        3 0  |   13.26588    .240342    55.20   0.000     12.79475      13.737
        3 1  |   25.90888   .7439926    34.82   0.000     24.45049    27.36727
        4 0  |   12.74739   .1759152    72.46   0.000     12.40255    13.09222
        4 1  |   26.21898   .5210829    50.32   0.000     25.19754    27.24042
        5 0  |    12.2289   .1131815   108.05   0.000     12.00704    12.45076
        5 1  |   26.52909   .3138487    84.53   0.000     25.91387     27.1443
        6 0  |   11.71041   .0579307   202.15   0.000     11.59685    11.82397
        6 1  |   26.83919   .1855954   144.61   0.000     26.47538      27.203
        7 0  |   11.19192   .0508319   220.18   0.000     11.09228    11.29156
        7 1  |   27.14929   .2817116    96.37   0.000     26.59707    27.70151
        8 0  |   10.67343   .1024393   104.19   0.000     10.47263    10.87424
        8 1  |   27.45939   .4829579    56.86   0.000     26.51269     28.4061
        9 0  |   10.15495   .1645775    61.70   0.000     9.832337    10.47756
        9 1  |    27.7695   .7043481    39.43   0.000     26.38882    29.15018
------------------------------------------------------------------------------

. marginsplot, scheme(s1color) ytitle("% Radical right") title("") ///
>         xtitle("(Log) distance nearest concentration camp") ///
>         ytitle("Predicted radical-right support") ///
>                 title("2017") ///
>          name(afd_2017, replace)        ///
>         plot( , label("West" "East"))

  Variables that uniquely identify margins: log_dist east

. 
. 
. graph combine afd_2013 afd_2017, scheme(s1color)

. 
end of do-file

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. graph export "figures_model_radicalvote.png", replace
(file figures_model_radicalvote.png written in PNG format)

. 
end of do-file

. sum p_radical_right_17

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
p_radi~ht_17 |     11,754    14.61603    7.737772          0   52.38095

. sum log_pop_density_17

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
log_pop_d~17 |     10,983    4.414946    .9984381   .8323443   7.997427

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. 
. label variable weighted_pnsda_1930 "% votes NSDA (1930)"

. label variable weighted_pcommunist_1930 "% votes Communists (1930)"

. 
end of do-file

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. twoway (scatter         p_radical weighted_pnsda_1930) (lfit    p_radical weighted_pnsda_1930), schem
> e(s1color) ///
>         ytitle("% votes radical right (2013)") name(scatter_radical, replace) legend(off)

. 
. twoway (scatter         p_radical_left weighted_pcommunist_1930) (lfit  p_radical_left weighted_pcomm
> unist_1930), scheme(s1color) ///
>         ytitle("% votes radical left (2013)") name(scatter_left, replace) legend(off)
variable p_radical_left not found
r(111);

end of do-file

r(111);

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. egen sum_radical_left = rsum(SECOND_MLPD SECOND_DIELINKE)

. gen p_radical_left = (sum_radical_left*100)/Second_total_cast
(6,641 missing values generated)

. 
end of do-file

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. twoway (scatter         p_radical weighted_pnsda_1930) (lfit    p_radical weighted_pnsda_1930), schem
> e(s1color) ///
>         ytitle("% votes radical right (2013)") name(scatter_radical, replace) legend(off)

. 
. twoway (scatter         p_radical_left weighted_pcommunist_1930) (lfit  p_radical_left weighted_pcomm
> unist_1930), scheme(s1color) ///
>         ytitle("% votes radical left (2013)") name(scatter_left, replace) legend(off)

. 
. graph combine   scatter_radical scatter_left,  graphregion(fcolor(white))

. 
end of do-file

. do "/var/folders/h2/b58rkcl92x3305yp9jfz7x680000gn/T//SD13612.000000"

. gen log_population_33 =  log(1 + weighted_population_33)
(6,503 missing values generated)

. 
. reg log_dist c.weighted_pnsda_1930 c.weighted_p_jews_25  c.weighted_p_factory_33 weighted_p_land_25 /
> //
>                 log_population_33 i.east , vce(cluster land_num)        

Linear regression                               Number of obs     =     11,104
                                                F(6, 15)          =       4.89
                                                Prob > F          =     0.0059
                                                R-squared         =     0.0514
                                                Root MSE          =       .719

                                       (Std. Err. adjusted for 16 clusters in land_num)
---------------------------------------------------------------------------------------
                      |               Robust
             log_dist |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
  weighted_pnsda_1930 |   .0006545    .003579     0.18   0.857    -.0069739    .0082829
   weighted_p_jews_25 |   .0491067   .1105378     0.44   0.663     -.186499    .2847124
weighted_p_factory_33 |   .0033232   .0081299     0.41   0.688    -.0140052    .0206517
   weighted_p_land_25 |     .00966   .0052466     1.84   0.085    -.0015228    .0208429
    log_population_33 |  -.0379974   .0110532    -3.44   0.004    -.0615568    -.014438
               1.east |   -.329703   .1444564    -2.28   0.037    -.6376045   -.0218016
                _cons |   9.725091   .4610804    21.09   0.000     8.742321    10.70786
---------------------------------------------------------------------------------------

. coefplot , drop(_cons) xline(0)  scheme(s1color) ///
>         coeflabels(weighted_pnsda_1930 = "% votes NSDA (1930)" weighted_p_jews_25 = "% Jewish populat
> ion (1930)" ///
>         weighted_p_factory_33 = "% factory workers (1933)" weighted_p_land_25 = "% land workers (1933
> )"   ///
>          log_population_33 = "(Log) Population density (1933)" 1.east= "East lander") ///
>         xtitle("Coefficients with 99 and 95% CI") levels(99 95)

. 
end of do-file

. clear

. exit
